Nursing homes and assisted care facilities employ a number of different methods and devices to monitor their patients. These devices are capable of monitoring physiological functions, but are generally used in isolation and not integrated with other devices. Some devices include fall alert buttons that require a patient to actively push a button to alert the staff of a care facility of a fall. This type of device, however, is not effective for a patient who has a cognitive impairment (such as dementia) is knocked unconscious or otherwise rendered incapacitated by a fall or other medical condition. Care facilities also use a variety of pressure pads and other sensors to provide an audible alert to indicate that a patient has left a desired location. These types of devices have reliability problems and require a high level of vigilance to constantly monitor the sensors. Moreover, none of these devices is capable of delivering private, targeted and configurable alerts for designated caregivers, nor do they provide centralized data collection for automatic charting and close monitoring of individual patients.
In addition to the above, many care facilities try to perform at least some vital sign monitoring. This may be limited to checking a patient's vital signs only once a week due to the time and cost required to have staff to perform these duties. However, when a patient's vital signs are checked only once a week, the declining health of a patient may only be detected after a health condition has worsened, eliminating the opportunity for early intervention. Thus, there can be an increase in a care facility's patient morbidity and mortality rate. Additionally, staff turnover and productivity can be an issue in care facilities that may need to spend more time replacing and training staff members to monitor sensors and patients' vital signs and to understand the patient's medical history and specific need for care.
Care facilities also have an interest in knowing the location of their patients at their facility, as well as patients that may be located remotely or living at individual homes and receiving care remotely. However, typical methods of monitoring patients and determining their locations involve the use of video cameras and closed-circuit television. Another method is the use of motion detectors to infer movement and activity level within a home. These systems typically require significant wiring or installation of equipment within a home and can be uneconomical for either home or multi-patient facility use. Moreover, motion detectors cannot distinguish between multiple residents or pets present in the home. Additionally, this may only provide an inference, but not a direct and objective indication, of the patient's well-being. Further, video-based services require a high level of attention to the video feeds from the cameras and the identity of the people can be difficult to discern. There are additional issues in personal privacy and intrusion when using video or even motion detectors. Additionally, it is not usually practical to have cameras or a video monitoring system in the house of a remotely located patient.
Other facilities, such as hospitals, have also utilized patient and personnel tracking systems using radio frequency identification (RFID) badges. These devices can be worn by a person and may be passive devices or may transmit an RF signal that may be tracked from a centralized location in the facility. These devices, however, do not provide any other information besides the location of the wearer and they may not provide adequate transmission range. Also, RFID is limited in its memory so very little processing is available and there is no 2-way processing of event monitoring data. Other information that a care facility may desire to collect, such as a patient's vital signs, are not collected or transmitted by these devices. Additionally, the battery life on these devices can vary significantly depending on the type of RF signal transmitted and the amount and duration of transmissions from the device. Typically the devices only have a battery life of a few hours or several days before they require recharging or replacing the batteries. Other devices designed to transmit a signal having information about a patient may utilize cellular phone technology. These devices, however, often fail to get an appropriate cellular signal inside health care facilities and again require significantly more power and have a battery life of hours thereby rendering such devices impractical for long-term monitoring.
Yet other devices that have been used in battery-powered sensors include those using IEEE 802.15.1 Bluetooth wireless technology to replace cables. Enabling devices with Bluetooth does not in itself bring about an integration of separate monitoring devices for one patient. Indeed, there can be a limit of eight devices that may be joined together in a Bluetooth pico-net raising the question about scaling and the capacity to support hundreds of patients in a facility. The short range, typically on the order of ten meters, calls for a multimode extensive network strategy to support a healthcare facility, such as a mesh or partial mesh network, would provide for adequate coverage but also exceeds the specifications of Bluetooth. Merely replacing a cable from a monitor to a wireless Bluetooth enabled equivalent can result in rapid battery depletion if continuous monitoring is attempted.
Still other devices have been used for monitoring a patient's vital signs. These devices have been wearable and typically were capable of monitoring some vital signs, such as pulse rate and body temperature. These devices, however, typically only have the ability to display the information collected on a display that is either worn on the patient or on separate display that the collected data is downloaded onto. Some devices that monitor vital signs, such as pulse rate, require the patient to be relatively still to obtain an accurate reading. Other devices have included the ability to transmit location information to track the movement of a patient. These devices, however, do not have the ability to transmit collected data on the patient back to a central location for analysis. Further, these devices usually require a patient to wear a variety of different sensors and can be intrusive on the patient, embarrassing to wear, and prohibit some movement. These devices also only allow a patient to wear the device for a limited time, for example a few hours to several days, before the power source must be replaced or recharged.
Therefore, a need exists for a system that can track and monitor a patient using a wearable, form-friendly, low-power, wireless device that can be used to monitor the health and wellness of a person wearing the device during the person's daily activities, over long periods of time without the need to recharge the device, and without the constant surveillance of healthcare personnel.
As the percentage of the U.S. population aged 65 and older wows, it is increasingly important that the many factors affecting the health and wellbeing of this population are understood and addressed. Almost 90% of the elderly suffer from at least one chronic illness such as congestive heart failure (CHF), diabetes, hypertension, or dementia, while 77% suffer from multiple chronic diseases that are particularly complex to manage. Methods of surveying this population's health status and gathering longitudinal data such as activity levels, sleep patterns, physiological data and behavior patterns are needed. Poor behaviors include, for example, lack of activity, a factor cited as one of the major causes of chronic disease and also lack of the capacity for self-care which can be indicative of issues with cognition, depression or other functional issues associated with independent living. Other factors include failure to take prescribed medications according to the recommended schedule. Decreased stability, as tracked over long periods of time, points to increased risk of falls. Trends and rapid changes in vital signs provide an important profile that contributes to overall wellness and management of risks within specific disease care plans.
To understand and track the health of the elderly and or patients managing chronic conditions, data is needed by researchers, health policy analysts and, on a more timely and intimate basis, the caregiver, the medical team following the patient, and the patients themselves. Systems capable of easily collecting real-time, yet subtle health and wellness changes provide automated and easier access to insights into these diseases by providing more careful observations of physiologic changes thereby enabling earlier intervention, prevention and the potential for significant cost reductions and improved outcomes.